Most analytic studies of human epidemiologic data have affirmed the linear association between excess lung cancer risk and airborne arsenic exposure. Recent Canadian analyses, however, based on the mortality follow-up of Tacoma smelter workers from 1940-1976, provided strong evidence of a nonlinear dose-response when lung cancer risk was expressed in terms of the standardized mortality ratio. Using recently updated data covering ten additional years of mortality experience among Tacoma workers (1940-1986), new analyses were undertaken to further explore nonlinearity in the lung cancer dose-response in this worker cohort. Lung cancer risk was expressed in terms of both the standardized mortality ratio (SMR) and the excess mortality rate (EMR). As in Canadian analyses, nonlinearity was assessed through a three parameter model containing both linear and negative exponential terms for dose. Dropping the negative-exponential dose-term lead to the standard suite of linear dose-response models, with and without intercept, used for comparative purposes. Analyses were undertaken by subcohort as there was strong evidence of confounding by year of initial hire, which largely explained the nonlinearity in the dose-response observed in Canadian analyses. Subcohort analyses based on initial employment, prior to 1940 or thereafter, showed that the nonlinearity in the dose-response was strongly influenced by date of initial hire. whether the cohort risk was measured by either the SMR or EMR, a nonlinear dose-response was evident only among workers hired prior to 1940. This, however, was strongly related to the artifactually low lung cancer mortality seen among workers hired between 1930 and 1939. Among workers hired after 1940, analyses showed that a linear dose-response provided a clearly superior fit. While analyses showed comparable goodness of fit when models were fitted to the SMR and EMR. Only those based on the EMR provided strong evidence of a dose-response. Overall, nonlinearity as observed in Canadian analyses was likely the result of several sources of bias not taken into account by Canadian investigators.
Copyright 1999 Academic Press.